Applications as above and many others have motivated a significant body of work in rare/weak feature models through the past two decades, providing fruitful insights for signal detection, feature selection, and classification problems in high dimensions [1]}. Specific examples of rare/weak features models include normal [2]}, [3]}, [4]}, [5]}, binomial mixtures [6]}, linear regression [7]}, [8]},
Poisson mixtures [9]}, heteroscedastic normal mixtures [10]}, general mixtures [11]}, and several two-sample settings [12]}.
